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Published on 15.07.15 in Vol 17, No 7 (2015): July

This paper is in the following e-collection/theme issue:

Works citing "Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study"

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.4273):

(note that this is only a small subset of citations)

  1. Gong J, Huang Y, Chow PI, Fua K, Gerber MS, Teachman BA, Barnes LE. Understanding behavioral dynamics of social anxiety among college students through smartphone sensors. Information Fusion 2019;49:57
    CrossRef
  2. Lee U, Han K, Cho H, Chung K, Hong H, Lee S, Noh Y, Park S, Carroll JM. Intelligent positive computing with mobile, wearable, and IoT devices: Literature review and research directions. Ad Hoc Networks 2019;83:8
    CrossRef
  3. Reinertsen E, Clifford GD. A review of physiological and behavioral monitoring with digital sensors for neuropsychiatric illnesses. Physiological Measurement 2018;39(5):05TR01
    CrossRef
  4. Barnett I, Torous J, Staples P, Sandoval L, Keshavan M, Onnela J. Relapse prediction in schizophrenia through digital phenotyping: a pilot study. Neuropsychopharmacology 2018;43(8):1660
    CrossRef
  5. Briffault X, Morgiève M, Courtet P. From e-Health to i-Health: Prospective Reflexions on the Use of Intelligent Systems in Mental Health Care. Brain Sciences 2018;8(6):98
    CrossRef
  6. Barrigón ML, Baca-García E. Retos actuales en la investigación en suicidio. Revista de Psiquiatría y Salud Mental 2018;11(1):1
    CrossRef
  7. Barnett I, Torous J, Staples P, Keshavan M, Onnela J. Beyond smartphones and sensors: choosing appropriate statistical methods for the analysis of longitudinal data. Journal of the American Medical Informatics Association 2018;
    CrossRef
  8. Berrouiguet S, Perez-Rodriguez MM, Larsen M, Baca-García E, Courtet P, Oquendo M. From eHealth to iHealth: Transition to Participatory and Personalized Medicine in Mental Health. Journal of Medical Internet Research 2018;20(1):e2
    CrossRef
  9. Kleiman EM, Nock MK. Real-time assessment of suicidal thoughts and behaviors. Current Opinion in Psychology 2018;22:33
    CrossRef
  10. Berrouiguet S, Ramirez D, Barrigon Estevez ML, Moreno-Munoz P, Carmona Camacho R, Baca-Garcia E, Artes-Rodriguez A. Combining continuous smartphone native sensors data capture and unsupervised data mining techniques for behavioral changes detection: The feasibility study of the Evidence Based Behavior (eB2) platform (Preprint). JMIR mHealth and uHealth 2018;
    CrossRef
  11. Sano A, Taylor S, McHill AW, Phillips AJ, Barger LK, Klerman E, Picard R. Identifying Objective Physiological Markers and Modifiable Behaviors for Self-Reported Stress and Mental Health Status Using Wearable Sensors and Mobile Phones: Observational Study. Journal of Medical Internet Research 2018;20(6):e210
    CrossRef
  12. Boonstra TW, Nicholas J, Wong QJ, Shaw F, Townsend S, Christensen H. Using Mobile Phone Sensor Technology for Mental Health Research: Integrated Analysis to Identify Hidden Challenges and Potential Solutions. Journal of Medical Internet Research 2018;20(7):e10131
    CrossRef
  13. Lu J, Bi J, Shang C, Yue C, Morillo R, Ware S, Kamath J, Bamis A, Russell A, Wang B. Joint Modeling of Heterogeneous Sensing Data for Depression Assessment via Multi-task Learning. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2018;2(1):1
    CrossRef
  14. Boukhechba M, Chow P, Fua K, Teachman BA, Barnes LE. Predicting Social Anxiety From Global Positioning System Traces of College Students: Feasibility Study. JMIR Mental Health 2018;5(3):e10101
    CrossRef
  15. Roberts LW, Chan S, Torous J. New tests, new tools: mobile and connected technologies in advancing psychiatric diagnosis. npj Digital Medicine 2018;1(1)
    CrossRef
  16. Price M, Van Stolk-Cooke K, Legrand AC, Brier ZMF, Ward HL, Connor JP, Gratton J, Freeman K, Skalka C. Implementing assessments via mobile during the acute posttrauma period: feasibility, acceptability and strategies to improve response rates. European Journal of Psychotraumatology 2018;9(sup1):1500822
    CrossRef
  17. Spaiser V, Luzzatti D, Gregoriou A, Ferrara E, Chadefaux T. Advancing sustainability: Using smartphones to study environmental behavior in a field-experimental setup. Data Science 2018;:1
    CrossRef
  18. Lind MN, Byrne ML, Wicks G, Smidt AM, Allen NB. The Effortless Assessment of Risk States (EARS) Tool: An Interpersonal Approach to Mobile Sensing. JMIR Mental Health 2018;5(3):e10334
    CrossRef
  19. Meng J, Hussain SA, Mohr DC, Czerwinski M, Zhang M. Exploring User Needs for a Mobile Behavioral-Sensing Technology for Depression Management: Qualitative Study. Journal of Medical Internet Research 2018;20(7):e10139
    CrossRef
  20. Zulueta J, Piscitello A, Rasic M, Easter R, Babu P, Langenecker SA, McInnis M, Ajilore O, Nelson PC, Ryan K, Leow A. Predicting Mood Disturbance Severity with Mobile Phone Keystroke Metadata: A BiAffect Digital Phenotyping Study. Journal of Medical Internet Research 2018;20(7):e241
    CrossRef
  21. Donker T, Van Esveld S, Fischer N, Van Straten A. 0Phobia – towards a virtual cure for acrophobia: study protocol for a randomized controlled trial. Trials 2018;19(1)
    CrossRef
  22. Frank E, Pong J, Asher Y, Soares CN. Smart phone technologies and ecological momentary data. Current Opinion in Psychiatry 2018;31(1):3
    CrossRef
  23. Goodspeed R, Yan X, Hardy J, Vydiswaran VV, Berrocal VJ, Clarke P, Romero DM, Gomez-Lopez IN, Veinot T. Comparing the Data Quality of Global Positioning System Devices and Mobile Phones for Assessing Relationships Between Place, Mobility, and Health: Field Study. JMIR mHealth and uHealth 2018;6(8):e168
    CrossRef
  24. Craske MG. Honoring the Past, Envisioning the Future: ABCT’s 50th Anniversary Presidential Address. Behavior Therapy 2018;49(2):151
    CrossRef
  25. Boukhechba M, Daros AR, Fua K, Chow PI, Teachman BA, Barnes LE. DemonicSalmon: Monitoring Mental Health and Social Interactions of College Students Using Smartphones. Smart Health 2018;
    CrossRef
  26. Scott SB, Munoz E, Mogle JA, Gamaldo AA, Smyth JM, Almeida DM, Sliwinski MJ. Perceived neighborhood characteristics predict severity and emotional response to daily stressors. Social Science & Medicine 2018;200:262
    CrossRef
  27. Bourla A, Mouchabac S, El Hage W, Ferreri F. e-PTSD: an overview on how new technologies can improve prediction and assessment of Posttraumatic Stress Disorder (PTSD). European Journal of Psychotraumatology 2018;9(sup1):1424448
    CrossRef
  28. Renn BN, Pratap A, Atkins DC, Mooney SD, Areán PA. Smartphone-based passive assessment of mobility in depression: Challenges and opportunities. Mental Health and Physical Activity 2018;14:136
    CrossRef
  29. Rohani DA, Tuxen N, Quemada Lopategui A, Kessing LV, Bardram JE. Data-Driven Learning in High-Resolution Activity Sampling From Patients With Bipolar Depression: Mixed-Methods Study. JMIR Mental Health 2018;5(2):e10122
    CrossRef
  30. Pratap A, Atkins DC, Renn BN, Tanana MJ, Mooney SD, Anguera JA, Areán PA. The accuracy of passive phone sensors in predicting daily mood. Depression and Anxiety 2018;
    CrossRef
  31. Balicer RD, Luengo-Oroz M, Cohen-Stavi C, Loyola E, Mantingh F, Romanoff L, Galea G. Using big data for non-communicable disease surveillance. The Lancet Diabetes & Endocrinology 2018;6(8):595
    CrossRef
  32. Suffoletto B, Scaglione S. Using Digital Interventions to Support Individuals with Alcohol Use Disorder and Advanced Liver Disease: A Bridge Over Troubled Waters. Alcoholism: Clinical and Experimental Research 2018;42(7):1160
    CrossRef
  33. Pratap A, Renn BN, Volponi J, Mooney SD, Gazzaley A, Arean PA, Anguera JA. Using Mobile Apps to Assess and Treat Depression in Hispanic and Latino Populations: Fully Remote Randomized Clinical Trial. Journal of Medical Internet Research 2018;20(8):e10130
    CrossRef
  34. Bourla A, Ferreri F, Ogorzelec L, Guinchard C, Mouchabac S. Évaluation des troubles thymiques par l’étude des données passives : le concept de phénotype digital à l’épreuve de la culture de métier de psychiatre. L'Encéphale 2018;44(2):168
    CrossRef
  35. Kennedy SH, Ceniti AK. Unpacking Major Depressive Disorder: From Classification to Treatment Selection. The Canadian Journal of Psychiatry 2018;63(5):308
    CrossRef
  36. Wu C, Boukhechba M, Cai L, Barnes LE, Gerber MS. Improving momentary stress measurement and prediction with bluetooth encounter networks. Smart Health 2018;
    CrossRef
  37. Shaffer JA, Kronish IM, Falzon L, Cheung YK, Davidson KW. N-of-1 Randomized Intervention Trials in Health Psychology: A Systematic Review and Methodology Critique. Annals of Behavioral Medicine 2018;52(9):731
    CrossRef
  38. Barrigón ML, Baca-García E. Current challenges in research on suicide. Revista de Psiquiatría y Salud Mental (English Edition) 2018;11(1):1
    CrossRef
  39. Rohani DA, Faurholt-Jepsen M, Kessing LV, Bardram JE. Correlations Between Objective Behavioral Features Collected From Mobile and Wearable Devices and Depressive Mood Symptoms in Patients With Affective Disorders: Systematic Review. JMIR mHealth and uHealth 2018;6(8):e165
    CrossRef
  40. Šimon M, Vašát P, Poláková M, Gibas P, Daňková H. Activity spaces of homeless men and women measured by GPS tracking data: A comparative analysis of Prague and Pilsen. Cities 2018;
    CrossRef
  41. Helbich M. Toward dynamic urban environmental exposure assessments in mental health research. Environmental Research 2018;161:129
    CrossRef
  42. Eichstaedt JC, Smith RJ, Merchant RM, Ungar LH, Crutchley P, Preoţiuc-Pietro D, Asch DA, Schwartz HA. Facebook language predicts depression in medical records. Proceedings of the National Academy of Sciences 2018;:201802331
    CrossRef
  43. Cornet VP, Holden RJ. Systematic review of smartphone-based passive sensing for health and wellbeing. Journal of Biomedical Informatics 2018;77:120
    CrossRef
  44. Becker D, van Breda W, Funk B, Hoogendoorn M, Ruwaard J, Riper H. Predictive modeling in e-mental health: A common language framework. Internet Interventions 2018;12:57
    CrossRef
  45. Place S, Blanch-Hartigan D, Rubin C, Gorrostieta C, Mead C, Kane J, Marx BP, Feast J, Deckersbach T, Pentland A, Nierenberg A, Azarbayejani A. Behavioral Indicators on a Mobile Sensing Platform Predict Clinically Validated Psychiatric Symptoms of Mood and Anxiety Disorders. Journal of Medical Internet Research 2017;19(3):e75
    CrossRef
  46. Bhugra D, Tasman A, Pathare S, Priebe S, Smith S, Torous J, Arbuckle MR, Langford A, Alarcón RD, Chiu HFK, First MB, Kay J, Sunkel C, Thapar A, Udomratn P, Baingana FK, Kestel D, Ng RMK, Patel A, Picker LD, McKenzie KJ, Moussaoui D, Muijen M, Bartlett P, Davison S, Exworthy T, Loza N, Rose D, Torales J, Brown M, Christensen H, Firth J, Keshavan M, Li A, Onnela J, Wykes T, Elkholy H, Kalra G, Lovett KF, Travis MJ, Ventriglio A. The WPA- Lancet Psychiatry Commission on the Future of Psychiatry. The Lancet Psychiatry 2017;4(10):775
    CrossRef
  47. Sarikaya R. The Technology Behind Personal Digital Assistants: An overview of the system architecture and key components. IEEE Signal Processing Magazine 2017;34(1):67
    CrossRef
  48. Palmius N, Tsanas A, Saunders KEA, Bilderbeck AC, Geddes JR, Goodwin GM, De Vos M. Detecting Bipolar Depression From Geographic Location Data. IEEE Transactions on Biomedical Engineering 2017;64(8):1761
    CrossRef
  49. Harari GM, Müller SR, Aung MS, Rentfrow PJ. Smartphone sensing methods for studying behavior in everyday life. Current Opinion in Behavioral Sciences 2017;18:83
    CrossRef
  50. Ram N, Brinberg M, Pincus AL, Conroy DE. The Questionable Ecological Validity of Ecological Momentary Assessment: Considerations for Design and Analysis. Research in Human Development 2017;14(3):253
    CrossRef
  51. Saeb S, Lattie EG, Kording KP, Mohr DC. Mobile Phone Detection of Semantic Location and Its Relationship to Depression and Anxiety. JMIR mHealth and uHealth 2017;5(8):e112
    CrossRef
  52. Webb CA, Rosso IM, Rauch SL. Internet-Based Cognitive-Behavioral Therapy for Depression. Harvard Review of Psychiatry 2017;25(3):114
    CrossRef
  53. Leonard NR, Silverman M, Sherpa DP, Naegle MA, Kim H, Coffman DL, Ferdschneider M. Mobile Health Technology Using a Wearable Sensorband for Female College Students With Problem Drinking: An Acceptability and Feasibility Study. JMIR mHealth and uHealth 2017;5(7):e90
    CrossRef
  54. Aguilera A, Bruehlman-Senecal E, Demasi O, Avila P. Automated Text Messaging as an Adjunct to Cognitive Behavioral Therapy for Depression: A Clinical Trial. Journal of Medical Internet Research 2017;19(5):e148
    CrossRef
  55. Torous J, Rodriguez J, Powell A. The New Digital Divide For Digital Biomarkers. Digital Biomarkers 2017;
    CrossRef
  56. Dogan E, Sander C, Wagner X, Hegerl U, Kohls E. Smartphone-Based Monitoring of Objective and Subjective Data in Affective Disorders: Where Are We and Where Are We Going? Systematic Review. Journal of Medical Internet Research 2017;19(7):e262
    CrossRef
  57. Bidargaddi N, Musiat P, Makinen V, Ermes M, Schrader G, Licinio J. Digital footprints: facilitating large-scale environmental psychiatric research in naturalistic settings through data from everyday technologies. Molecular Psychiatry 2017;22(2):164
    CrossRef
  58. DeMasi O, Kording K, Recht B, Jan Y. Meaningless comparisons lead to false optimism in medical machine learning. PLOS ONE 2017;12(9):e0184604
    CrossRef
  59. Malhi GS, Hamilton A, Morris G, Mannie Z, Das P, Outhred T. The promise of digital mood tracking technologies: are we heading on the right track?. Evidence Based Mental Health 2017;20(4):102
    CrossRef
  60. Cuttone A, Bækgaard P, Sekara V, Jonsson H, Larsen JE, Lehmann S, Zhou W. SensibleSleep: A Bayesian Model for Learning Sleep Patterns from Smartphone Events. PLOS ONE 2017;12(1):e0169901
    CrossRef
  61. Bauer M, Glenn T, Monteith S, Bauer R, Whybrow PC, Geddes J. Ethical perspectives on recommending digital technology for patients with mental illness. International Journal of Bipolar Disorders 2017;5(1)
    CrossRef
  62. Chow PI, Fua K, Huang Y, Bonelli W, Xiong H, Barnes LE, Teachman BA. Using Mobile Sensing to Test Clinical Models of Depression, Social Anxiety, State Affect, and Social Isolation Among College Students. Journal of Medical Internet Research 2017;19(3):e62
    CrossRef
  63. Aung MH, Matthews M, Choudhury T. Sensing behavioral symptoms of mental health and delivering personalized interventions using mobile technologies. Depression and Anxiety 2017;34(7):603
    CrossRef
  64. Turvey C, Fortney J. The Use of Telemedicine and Mobile Technology to Promote Population Health and Population Management for Psychiatric Disorders. Current Psychiatry Reports 2017;19(11)
    CrossRef
  65. Torous J, Levin ME, Ahern DK, Oser ML. Cognitive Behavioral Mobile Applications: Clinical Studies, Marketplace Overview, and Research Agenda. Cognitive and Behavioral Practice 2017;24(2):215
    CrossRef
  66. Stachl C, Hilbert S, Au J, Buschek D, De Luca A, Bischl B, Hussmann H, Bühner M, Wrzus C. Personality Traits Predict Smartphone Usage. European Journal of Personality 2017;31(6):701
    CrossRef
  67. Mohr DC, Zhang M, Schueller SM. Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning. Annual Review of Clinical Psychology 2017;13(1):23
    CrossRef
  68. Bruehlman-Senecal E, Aguilera A, Schueller SM. Mobile Phone–Based Mood Ratings Prospectively Predict Psychotherapy Attendance. Behavior Therapy 2017;48(5):614
    CrossRef
  69. Fairburn CG, Patel V. The impact of digital technology on psychological treatments and their dissemination. Behaviour Research and Therapy 2017;88:19
    CrossRef
  70. Tuarob S, Tucker CS, Kumara S, Giles CL, Pincus AL, Conroy DE, Ram N. How are you feeling?: A personalized methodology for predicting mental states from temporally observable physical and behavioral information. Journal of Biomedical Informatics 2017;68:1
    CrossRef
  71. Aledavood T, Triana Hoyos AM, Alakörkkö T, Kaski K, Saramäki J, Isometsä E, Darst RK. Data Collection for Mental Health Studies Through Digital Platforms: Requirements and Design of a Prototype. JMIR Research Protocols 2017;6(6):e110
    CrossRef
  72. Harari GM, Müller SR, Mishra V, Wang R, Campbell AT, Rentfrow PJ, Gosling SD. An Evaluation of Students’ Interest in and Compliance With Self-Tracking Methods. Social Psychological and Personality Science 2017;8(5):479
    CrossRef
  73. Faherty LJ, Hantsoo L, Appleby D, Sammel MD, Bennett IM, Wiebe DJ. Movement patterns in women at risk for perinatal depression: use of a mood-monitoring mobile application in pregnancy. Journal of the American Medical Informatics Association 2017;24(4):746
    CrossRef
  74. Saeb S, Cybulski TR, Kording KP, Mohr DC. Scalable Passive Sleep Monitoring Using Mobile Phones: Opportunities and Obstacles. Journal of Medical Internet Research 2017;19(4):e118
    CrossRef
  75. Saeb S, Lonini L, Jayaraman A, Mohr DC, Kording KP. The need to approximate the use-case in clinical machine learning. GigaScience 2017;6(5)
    CrossRef
  76. Johansen B, Petersen M, Korzepa M, Larsen J, Pontoppidan N, Larsen J. Personalizing the Fitting of Hearing Aids by Learning Contextual Preferences From Internet of Things Data. Computers 2017;7(1):1
    CrossRef
  77. Sabharwal A, Veeraraghavan A. Bio-Behavioral Sensing. GetMobile: Mobile Computing and Communications 2017;21(3):11
    CrossRef
  78. DeMasi O, Feygin S, Dembo A, Aguilera A, Recht B. Well-Being Tracking via Smartphone-Measured Activity and Sleep: Cohort Study. JMIR mHealth and uHealth 2017;5(10):e137
    CrossRef
  79. Low CA, Dey AK, Ferreira D, Kamarck T, Sun W, Bae S, Doryab A. Estimation of Symptom Severity During Chemotherapy From Passively Sensed Data: Exploratory Study. Journal of Medical Internet Research 2017;19(12):e420
    CrossRef
  80. Wang W. Smartphones as Social Actors? Social dispositional factors in assessing anthropomorphism. Computers in Human Behavior 2017;68:334
    CrossRef
  81. Mandryk RL, Birk MV. Toward Game-Based Digital Mental Health Interventions: Player Habits and Preferences. Journal of Medical Internet Research 2017;19(4):e128
    CrossRef
  82. Luhmann M. Using Big Data to study subjective well-being. Current Opinion in Behavioral Sciences 2017;18:28
    CrossRef
  83. Armontrout J, Torous J, Fisher M, Drogin E, Gutheil T. Mobile Mental Health: Navigating New Rules and Regulations for Digital Tools. Current Psychiatry Reports 2016;18(10)
    CrossRef
  84. Otte C, Gold SM, Penninx BW, Pariante CM, Etkin A, Fava M, Mohr DC, Schatzberg AF. Major depressive disorder. Nature Reviews Disease Primers 2016;2:16065
    CrossRef
  85. Torous J, Kiang MV, Lorme J, Onnela J. New Tools for New Research in Psychiatry: A Scalable and Customizable Platform to Empower Data Driven Smartphone Research. JMIR Mental Health 2016;3(2):e16
    CrossRef
  86. Arean PA, Hallgren KA, Jordan JT, Gazzaley A, Atkins DC, Heagerty PJ, Anguera JA. The Use and Effectiveness of Mobile Apps for Depression: Results From a Fully Remote Clinical Trial. Journal of Medical Internet Research 2016;18(12):e330
    CrossRef
  87. Wicks P, Hotopf M, Narayan VA, Basch E, Weatherall J, Gray M. It’s a long shot, but it just might work! Perspectives on the future of medicine. BMC Medicine 2016;14(1)
    CrossRef
  88. Aung MSH, Alquaddoomi F, Hsieh C, Rabbi M, Yang L, Pollak JP, Estrin D, Choudhury T. Leveraging Multi-Modal Sensing for Mobile Health: A Case Review in Chronic Pain. IEEE Journal of Selected Topics in Signal Processing 2016;10(5):962
    CrossRef
  89. Saeb S, Lattie EG, Schueller SM, Kording KP, Mohr DC. The relationship between mobile phone location sensor data and depressive symptom severity. PeerJ 2016;4:e2537
    CrossRef
  90. Hird N, Ghosh S, Kitano H. Digital health revolution: perfect storm or perfect opportunity for pharmaceutical R&D?. Drug Discovery Today 2016;21(6):900
    CrossRef
  91. Huguet A, Rao S, McGrath PJ, Wozney L, Wheaton M, Conrod J, Rozario S, Choo KR. A Systematic Review of Cognitive Behavioral Therapy and Behavioral Activation Apps for Depression. PLOS ONE 2016;11(5):e0154248
    CrossRef
  92. Wahle F, Kowatsch T, Fleisch E, Rufer M, Weidt S. Mobile Sensing and Support for People With Depression: A Pilot Trial in the Wild. JMIR mHealth and uHealth 2016;4(3):e111
    CrossRef
  93. Christensen MA, Bettencourt L, Kaye L, Moturu ST, Nguyen KT, Olgin JE, Pletcher MJ, Marcus GM, Romigi A. Direct Measurements of Smartphone Screen-Time: Relationships with Demographics and Sleep. PLOS ONE 2016;11(11):e0165331
    CrossRef
  94. Asselbergs J, Ruwaard J, Ejdys M, Schrader N, Sijbrandij M, Riper H. Mobile Phone-Based Unobtrusive Ecological Momentary Assessment of Day-to-Day Mood: An Explorative Study. Journal of Medical Internet Research 2016;18(3):e72
    CrossRef
  95. Kamilaris A, Pitsillides A. Mobile Phone Computing and the Internet of Things: A Survey. IEEE Internet of Things Journal 2016;3(6):885
    CrossRef
  96. Kirchner TR, Shiffman S. Spatio-temporal determinants of mental health and well-being: advances in geographically-explicit ecological momentary assessment (GEMA). Social Psychiatry and Psychiatric Epidemiology 2016;51(9):1211
    CrossRef
  97. Kang Y. Ontology Components for the Depression Management based on Context. Journal of the Korea Institute of Information and Communication Engineering 2016;20(9):1785
    CrossRef
  98. Harari GM, Lane ND, Wang R, Crosier BS, Campbell AT, Gosling SD. Using Smartphones to Collect Behavioral Data in Psychological Science. Perspectives on Psychological Science 2016;11(6):838
    CrossRef
  99. Suffoletto B, Aguilera A. Expanding Adolescent Depression Prevention Through Simple Communication Technologies. Journal of Adolescent Health 2016;59(4):373
    CrossRef
  100. Hung GC, Yang P, Chang C, Chiang J, Chen Y. Predicting Negative Emotions Based on Mobile Phone Usage Patterns: An Exploratory Study. JMIR Research Protocols 2016;5(3):e160
    CrossRef
  101. Miloff A, Marklund A, Carlbring P. The challenger app for social anxiety disorder: New advances in mobile psychological treatment. Internet Interventions 2015;2(4):382
    CrossRef
  102. Aledavood T, Lehmann S, Saramäki J. Digital daily cycles of individuals. Frontiers in Physics 2015;3
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/jmir.4273)

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  1. Thakur SS, Roy RB. Computational Intelligence: Theories, Applications and Future Directions - Volume I. 2019. Chapter 10:119
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  2. Derksen JJL. Preventie psychische aandoeningen. 2018. Chapter 2:31
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  3. Lee H, Cho A, Jo Y, Whang M. Advances in Computer Science and Ubiquitous Computing. 2018. Chapter 212:1332
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  4. Lee H, Jo Y, Kim H, Whang M. Advances in Computer Science and Ubiquitous Computing. 2018. Chapter 219:1377
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  5. Wolfer J. Online Engineering & Internet of Things. 2018. Chapter 63:672
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  6. Singh VK, Ghosh I. Encyclopedia of Behavioral Medicine. 2018. Chapter 102005-1:1
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  7. Cho A, Lee H, Hwang H, Jo Y, Whang M. Advances in Computer Science and Ubiquitous Computing. 2018. Chapter 218:1371
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  8. Castro LA, Rodríguez MD, Martínez F, Rodríguez L, Andrade G, Cornejo R. Intelligent Data Sensing and Processing for Health and Well-Being Applications. 2018. :3
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  9. Duke , Montag C. Internet Addiction. 2017. Chapter 21:359
    CrossRef
  10. Rabbi M, Hane Aung M, Choudhury T. Mobile Health. 2017. Chapter 26:519
    CrossRef
  11. Klaas VC, Calatroni A, Hardegger M, Guckenberger M, Theile G, Tröster G. Wireless Mobile Communication and Healthcare. 2017. Chapter 28:207
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  12. Vayena E, Gasser U. The Ethics of Biomedical Big Data. 2016. Chapter 2:17
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  13. Losada DE, Crestani F. Experimental IR Meets Multilinguality, Multimodality, and Interaction. 2016. Chapter 3:28
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